Functional network connectivity during rest and task conditions: A comparative study |
| |
Authors: | Mohammad R. Arbabshirani Martin Havlicek Kent A. Kiehl Godfrey D. Pearlson Vince D. Calhoun |
| |
Affiliation: | 1. The Mind Research Network, , Albuquerque, New Mexico;2. Department of ECE, University of New Mexico, , Albuquerque, New Mexico;3. Department of Psychology and Neuroscience, University of New Mexico, , Albuquerque, New Mexico;4. Olin Neuropsychiatry Research Center, Hartford Connecticut, , Hartford, Connecticut;5. Department of Psychiatry, Yale University School of Medicine, , New Haven, Connecticut |
| |
Abstract: | Functional connectivity (FC) examines temporal statistical dependencies among distant brain regions by means of seed‐based analysis or independent component analysis (ICA). Spatial ICA also makes it possible to investigate FC at the network level, termed functional network connectivity (FNC). The dynamics of each network (ICA component), which may consist of several remote regions is described by the ICA time‐course of that network; hence, FNC studies statistical dependencies among ICA time‐courses. In this article, we compare comprehensively FNC in the resting state and during performance of an auditory oddball (AOD) task in 28 healthy subjects on relevant (nonartifactual) brain networks. The results show global FNC decrease during the performance of the task. In addition, we show that specific networks enlarge and/or demonstrate higher activity during the performance of the task. The results suggest that performing an active task like AOD may be facilitated by recruiting more neurons and higher activation of related networks rather than collaboration among different brain networks. We also evaluated the impact of temporal filtering on FNC analyses. Results showed that the results are not significantly affected by filtering. Hum Brain Mapp 34:2959–2971, 2013. © 2012 Wiley Periodicals, Inc. |
| |
Keywords: | fMRI functional network connectivity independent component analysis |
|
|